Machine learning in predictive maintenance of industrial robots bei ABB

Join ABB and work in a team that is dedicated to creating a future where innovative digital technologies allow greater access to cleaner energy.

Predictive maintenance for industrial robots is a highly valuable service that can assist the customer in scheduling appropriate maintenance actions to prevent otherwise costly downtime. Connecting thousands of industrial robots globally to the cloud, the ABB AbilityTM Connected Services is a solution that pushes the robot industry within digitalization. The solution we offer our customers to provide services such as remote condition monitoring and asset optimization to improve the operation and maintenance of robots.
This thesis will explore predictive methods to extend existing algorithms that estimate the wear in robots and external equipment. To your help, you will have access to advanced physics simulations of our robots to produce high-quality data, enabling the use of machine learning and deep learning methods. The thesis can be conducted by a pair of students with individual sub-focuses and contributions i.e. focus on the fulfillment of functional and non-functional requirements respectively.

Your responsibilities

Extensive literature study in the field of predictive and condition-based maintenance, to understand the current trends and state of art.

Develop and benchmark different algorithms to predict the robot’s future wear.

Set up the simulation environment with our physics-engine to produce input data to be used by the algorithms.

Build a prototype or propose how the recommended solution could be integrated as an application in ABB AbilityTM Connected Services.

Your background

Engineering student within Computer Science, Industrial Engineering and Management, Information Technology, Applied Physics, System Engineering, or another program with a similar profile.

Comfortable working with systems and programming in a hobby, university, or professional context.

Curious and eager to learn.

More about us

Bring your very own sense of pride and purpose as you help us drive forward the Fourth Industrial Revolution – creating a sustainable future for our planet, and your career. Join ABB and harness the power of our diverse global network, as you collaborate with and learn from our world-class teams. Above all, challenge yourself every day. Let’s write the future, together.
Recruiting Manager Christer Mildton, christer.mildton@se.abb.com, will answer your questions. Union representatives - Sveriges Ingenjörer: Nicolin Ahlqvist, +4621-34 42 50, Unionen: Roger L. Gustavsson, +4621-32 90 97, Ledarna: Lenny Larsson, +4621-32 85 47.
Apply with your CV, academic transcripts, and a cover letter in English via our Career portal. Welcome to apply!

Reference Number

SE76352021_E1

Achtung: In der Regel brauchst du die Genehmigung deiner Uni oder eines Betreuers, damit die Projekt- oder Abschlussarbeit auf Graduateland als Teil deines Studiums anerkannt wird. Bitte setz dich rechtzeitig mit den richtigen Stellen in Verbindung, damit du sicher das richtige Projekt auswählen kannst.